A gamified e-learning web application with ai-driven study planner utilizing llama
E-learning has transformed the way of traditional learning by making learning accessible for students anywhere and anytime with technology devices. Thus, the project focuses on developing a gamified e-learning web application powered by artificial intelligence (AI) using Large Language Models (LLMs)...
Saved in:
| Main Author: | |
|---|---|
| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2025
|
| Subjects: | |
| Online Access: | http://eprints.utar.edu.my/7277/1/SE_2104483_FYP_report_%2D_TeyYuJing_TEY_YU_JING.pdf http://eprints.utar.edu.my/7277/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1855616548123705344 |
|---|---|
| author | Tey, Yu Jing |
| author_facet | Tey, Yu Jing |
| author_sort | Tey, Yu Jing |
| building | UTAR Library |
| collection | Institutional Repository |
| content_provider | Universiti Tunku Abdul Rahman |
| content_source | UTAR Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | E-learning has transformed the way of traditional learning by making learning accessible for students anywhere and anytime with technology devices. Thus, the project focuses on developing a gamified e-learning web application powered by artificial intelligence (AI) using Large Language Models (LLMs) integrated with LangChain for secondary school students to improve the learning experience. The web application is built using the Model-View-Controller (MVC) architecture, with Laravel for the backend and React for the front end. The three user modules, students, teachers, and administrators, are included to provide role-specific functionalities. Students can enroll in courses, access learning materials, engage in gamified challenges, track their learning progress, and participate in discussion forums. They also benefit from personalized AI-generated study plan timetables that analyze their strengths and weaknesses across subjects. Experimental results show that LLaMA 3.1 achieves higher accuracy and stability than Qwen 2.5, making it a stronger candidate for AI-driven study planning. Teachers are able to manage course content, monitor student performance, provide feedback, and interact with students, while administrators oversee user management, platform usage, and gamification elements. By combining gamification with AI-driven personalization, the web application aims to motivate students for more engagement to improve learning retention.
Keywords: Artificial Intelligence, E-Learning, Gamification, Large Language Models (LLMs), LLaMA, Personalized Learning
Subject Area: AZ191-193 Evaluation, LB1603-1696.6 Secondary education. High schools, T61-173 Technical education. Technical schools |
| format | Final Year Project / Dissertation / Thesis |
| id | my-utar-eprints.7277 |
| institution | Universiti Tunku Abdul Rahman |
| publishDate | 2025 |
| record_format | eprints |
| spelling | my-utar-eprints.72772026-01-13T10:00:44Z A gamified e-learning web application with ai-driven study planner utilizing llama Tey, Yu Jing QA76 Computer software T Technology (General) E-learning has transformed the way of traditional learning by making learning accessible for students anywhere and anytime with technology devices. Thus, the project focuses on developing a gamified e-learning web application powered by artificial intelligence (AI) using Large Language Models (LLMs) integrated with LangChain for secondary school students to improve the learning experience. The web application is built using the Model-View-Controller (MVC) architecture, with Laravel for the backend and React for the front end. The three user modules, students, teachers, and administrators, are included to provide role-specific functionalities. Students can enroll in courses, access learning materials, engage in gamified challenges, track their learning progress, and participate in discussion forums. They also benefit from personalized AI-generated study plan timetables that analyze their strengths and weaknesses across subjects. Experimental results show that LLaMA 3.1 achieves higher accuracy and stability than Qwen 2.5, making it a stronger candidate for AI-driven study planning. Teachers are able to manage course content, monitor student performance, provide feedback, and interact with students, while administrators oversee user management, platform usage, and gamification elements. By combining gamification with AI-driven personalization, the web application aims to motivate students for more engagement to improve learning retention. Keywords: Artificial Intelligence, E-Learning, Gamification, Large Language Models (LLMs), LLaMA, Personalized Learning Subject Area: AZ191-193 Evaluation, LB1603-1696.6 Secondary education. High schools, T61-173 Technical education. Technical schools 2025 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/7277/1/SE_2104483_FYP_report_%2D_TeyYuJing_TEY_YU_JING.pdf Tey, Yu Jing (2025) A gamified e-learning web application with ai-driven study planner utilizing llama. Final Year Project, UTAR. http://eprints.utar.edu.my/7277/ |
| spellingShingle | QA76 Computer software T Technology (General) Tey, Yu Jing A gamified e-learning web application with ai-driven study planner utilizing llama |
| title | A gamified e-learning web application with ai-driven study planner utilizing llama |
| title_full | A gamified e-learning web application with ai-driven study planner utilizing llama |
| title_fullStr | A gamified e-learning web application with ai-driven study planner utilizing llama |
| title_full_unstemmed | A gamified e-learning web application with ai-driven study planner utilizing llama |
| title_short | A gamified e-learning web application with ai-driven study planner utilizing llama |
| title_sort | gamified e-learning web application with ai-driven study planner utilizing llama |
| topic | QA76 Computer software T Technology (General) |
| url | http://eprints.utar.edu.my/7277/1/SE_2104483_FYP_report_%2D_TeyYuJing_TEY_YU_JING.pdf http://eprints.utar.edu.my/7277/ |
| url_provider | http://eprints.utar.edu.my |